Adaptability and stability of early carioca beans by mixed models
DOI:
https://doi.org/10.14393/BJ-v36n0a2020-48288Keywords:
Genotype x environment interaction, Phaseolus vulgaris L., Predicted genotypic values, REML/BLUP.Abstract
The genotype x environment interaction represents one of the major selection challenges due to the difficulty in identifying effectively superior genotypes. The present study aimed at estimating genetic parameters and selecting genotypes of early Carioca beans by analyzing simultaneous attributes, including yield, adaptability, and stability. In the agricultural year of 2015 and 2016, three trials were conducted, using a randomized block design, with three repetitions each, in the Agreste and Sertao regions of Pernambuco State. The genetic parameters were estimated using the mixed model procedure, and the selection was based on the harmonic mean of the relative performance of genetic values (MHPRVG, abbreviation in Portuguese) method. The environments influenced the phenotypic expression of the bean genotypes during both years, setting a specific adaptation. The mean heritability of the genotypes regarding yield exhibited low magnitude values in the trials of 2015 (5.78%) and 2016 (13.77%), indicating costly conditions for the selection of the improved genotypes. Genotype CNFC 15856 was selected, considering the genetic gain predicted for yield, by the average and specific performance in the three environments, and by the simultaneous attributes of yield, adaptability, and stability. The MHPRVG method enables the optimized selection of genotypes considering yield, stability, and adaptability; therefore, it should be included in the recommended selective criteria for agronomically superior genotypes in commercial plantations.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Thalyson Vasconcelos Lima, Paulo Ricardo dos Santos, Tâmara Rebecca Albuquerque de Oliveira, Maxwel Rodrigues Nascimento, kleyton Danilo da Silva Costa, Antônio Félix da Costa, Katiane da Rosa Gomes da Silva, Thiago Lívio Pessoa Oliveira, Emmanuelle Rodrigues Araújo, José Wilson da Silva
This work is licensed under a Creative Commons Attribution 4.0 International License.